Mr. Feng-Lien Wang Profile

Feng-Lien Wang

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Proceedings Article | 26 April 2020 Presentation + Paper

Terahertz LASSO compressed sensing tomography system

Khine Thin Zar Htun, Bo-Yi Wu, Feng-Lien Wang, Yi-Chun Hung, Shang-Hua Yang

Proceedings Volume 11348, 113480O (2020) https://doi.org/10.1117/12.2555749

KEYWORDS: 3D image reconstruction, Imaging systems, Terahertz radiation, Reconstruction algorithms, Compressed sensing, Modulation, Image restoration, Photomasks, Image quality, Tomography

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Terahertz imaging system has aroused great attentions in recent years due to its unique applications in security screening, industrial inspection and biomedical evaluation. Most conventional terahertz PCA imaging setup is based on raster scan method, hence, image acquisition time is severely limited by the speed of mechanical movement. Typically, image acquisition time of terahertz PCA tomography systems costs hours to days depending on the size of observed objects, which severely limits their practical feasibility to real-world applications. Here, we propose a terahertz least absolute shrinkage and selection operator (LASSO) compressed sensing (CS) tomography system to reduce more than one order of magnitude of data acquisition time. Our approach replaces slow-moving mechanical raster scanning method by the highspeed spatial modulation of terahertz radiation with designed patterns, resulting in a compact, fast and noise-reduced way to obtain terahertz 3D image dataset. Based on the measured dataset, modified Hadamard and LASSO algorithms are designed to reconstruct high-quality 3D image (voxel number: 128x128x128) in 120s at 10% compressed rate. The reconstructed LASSO 3D terahertz image offers a less than 0.002 mean squared error and 80% structural similarity index compared with the ground truth image. This paves the way toward real-time terahertz 3D imaging in near future, which opens the door for varies of exciting applications in non-destructive sensing, imaging and material inspection.

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